LAUSR

Abstract Recently, a powerful lifetime improvement algorithm for mobile wireless sensor networks has been reported in the literature. It controls the communication activity between the sensor nodes and the sink node through the solution of a simple convex optimization problem. In this article, a systemic performance assessment of this algorithm is carried out, taking into consideration that: i) The energy storage devices of the sensor nodes are subjected to recharge via radiative wireless power transfer events, ii) the node mobility patterns are governed by the random waypoint, the random Gauss–Markov, and the reference point group models, iii) a two-slope distance-dependent propagation path loss prediction model governs the energy consumption and the amount of recharge delivered to the sensor nodes, and iv) recharge takes place via omnidirectional and directional radiation patterns. Proper modeling and a large number of computer simulation results are presented and discussed. The factorial analysis of variance is applied to analyze the results, measuring individual and interaction effects of the node mobility patterns, the path loss models and the recharge mechanisms on the optimized network lifetime. Among the reported findings, some are worth highlighting: i) Different mobility patterns may result in considerably dissimilar performances of the adopted lifetime optimization strategy; ii) the adoption of the two-slope propagation loss model unveiled the need for developing efficient recharge mechanisms to cope with the potentially inefficient recharges that might happen when the target nodes are far away from the charger; iii) a poorly designed recharge mechanism might not bring sufficient lifetime improvement or sustained network operation.